SoroushVahidi/scidocs huggingface dataset:
Believable Social and Emotional Agents.
(1996)

One of the key steps in creating quality interactive drama is the ability to create quality interactive characters (or believable agents). Two important aspects of such characters will be that they appear emotional and that they can engage in social interactions. My basic approach to these problems has been to use a broad agent architecture and minimal amounts of modeling of other agent in the environment. This approach is based on an understanding of the artistic nature of the problem. To enable agent-builders (artists) to create emotional agents, I provide a general framework for building emotional agents, default emotion-processing rules, and discussion about how to create quality, emotional characters. My framework gets a lot of its power from being part of a broad agent architecture. The concept is simple: the agent will be emotionally richer if there are more things to have emotions about and more ways to express them. This reliance on breadth has also meant that I have been able to create simple emotion models that rely on perception and motivation instead of deep modeling of other agents and complex cognitive processing. To enable agent builders to create social behaviors for believable agents, I have designed a methodology that provides heuristics for incorporating personality into social behaviors and suggests how to model other agents in the environment. I propose an approach to modeling other agents that calls for limiting the amount of modeling of other agents to that which is sufficient to create the desired behavior. Using this technique, I have been able to build robust social behaviors that use surprisingly little representation. I have used this methodology to build a number of social behaviors, like negotiation and making friends. I have built three simulations containing seven agents to drive and test this work. I have also conducted user studies to demonstrate that these agents appear to be emotional and can engage in non-trivial social interactions while also being good characters with distinct personalities.
An Oz-Centric Review of Interactive Drama and Believable Agents
(1999)

Believable agents are autonomous agents that exhibit rich personalities. Interactive dramas take place in virtual worlds inhabited by characters (believable agents) with whom an audience interacts. In the course of this interaction, the audience experiences a story (lives a plot arc). This report presents the research philosophy behind the Oz Project, a research group at CMU that has spent the last ten years studying believable agents and interactive drama. The report then surveys current work from an Oz perspective. This research was partially supported by a grant from Intel Corporation. The views and conclusions contained in this document are those of the author and should not be interpreted as representing the official policies, either expressed or implied, of Intel Corporation.
Multi-level direction of autonomous creatures for real-time virtual environments
(1995)

There have been several recent efforts to build behavior-based autonomous creatures. While competent autonomous action is highly desirable, there is an important need to integrate autonomy with “directability”. In this paper we discuss the problem of building autonomous animated creatures for interactive virtual environments which are also capable of being directed at multiple levels. We present an approach to control which allows an external entity to “direct” an autonomous creature at the motivational level, the task level, and the direct motor level. We also detail a layered architecture and a general behavioral model for perception and action-selection which incorporates explicit support for multi-level direction. These ideas have been implemented and used to develop several autonomous animated creatures.
Integrating Reactive and Scripted Behaviors in a Life-Like Presentation Agent
(1998)

1. ABSTRACT Animated agents based either on real video, cartoon-style drawings or even model-based 3D graphics offer great promise for computer-based presentations as they make presentations more lively and appealing and allow for the emulation of conversation styles known from human-human communication. In this paper, we describe a life-like interface agent which presents multimedia material to the user following the directives of a script. The overall behavior of the presentation agent is partly determined by such a script, and partly by the agent's self-behavior. In our approach, the agent's behavior is defined in a declarative specification language. Behavior specifications are used to automatically generate a control module for an agent display system. The first part of the paper describes the generation process which involves AI planning and a two-step compilation. Since the manual creation of presentation scripts is tedious and error-prone, we also address the automated generation of presentation scripts which may be forwarded to the interface agent. The second part of the paper presents an approach for multimedia presentation design which combines hierarchical planning with temporal reasoning.
A Review on Facial Micro-Expressions Analysis: Datasets, Features and Metrics
(2018)

Facial micro-expressions are very brief, spontaneous facial expressions that appear on the face of humans when they either deliberately or unconsciously conceal an emotion. Micro-expression has shorter duration than macro-expression, which makes it more challenging for human and machine. Over the past ten years, automatic micro-expressions recognition has attracted increasing attention from researchers in psychology, computer science, security, neuroscience and other related disciplines. The aim of this paper is to provide the insights of automatic micro-expressions analysis and recommendations for future research. There has been a lot of datasets released over the last decade that facilitated the rapid growth in this field. However, comparison across different datasets is difficult due to the inconsistency in experiment protocol, features used and evaluation methods. To address these issues, we review the datasets, features and the performance metrics deployed in the literature. Relevant challenges such as the spatial temporal settings during data collection, emotional classes versus objective classes in data labelling, face regions in data analysis, standardisation of metrics and the requirements for real-world implementation are discussed. We conclude by proposing some promising future directions to advancing micro-expressions research.
Nexus : A GPU Cluster for Accelerating Neural Networks for Video Analysis
(2018)

We address the problem of serving Deep Neural Networks (DNNs) efficiently from a cluster of GPUs. In order to realize the promise of very low-cost processing made by accelerators such as GPUs, it is essential to run them at sustained high utilization. Doing so requires cluster-scale resource management that performs detailed scheduling of GPUs, reasoning about groups of DNN invocations that need to be co-scheduled, and moving from the conventional whole-DNN execution model to executing fragments of DNNs. Nexus is a fully implemented system that includes these innovations. On large-scale case studies on 16 GPUs, Nexus shows 1.8-41× better throughput than state-of-the-art systems while staying within latency constraints >99% of the time.
A Comprehensive Data Quality Methodology for Web and Structured Data
(2006)

Measuring and improving data quality in an organization or in a group of interacting organizations is a complex task. Several methodologies have been developed in the past providing a basis for the definition of a complete data quality program applying assessment and improvement techniques in order to guarantee high data quality levels. Since the main limitation of existing approaches is their specialization on specific issues or contexts, this paper presents the comprehensive data quality (CDQ) methodology that aims at integrating and enhancing the phases, techniques and tools proposed by previous approaches. CDQ methodology is conceived to be at the same time complete, flexible and simple to apply. Completeness is achieved by considering existing techniques and tools and integrating them in a framework that can work in both intra and inter organizational contexts, and can be applied to all types of data. The methodology is flexible since it supports the user in the selection of the most suitable techniques and tools within each phase and in any context. Finally, CDQ is simple since it is organized in phases and each phase is characterized by a specific goal and techniques to apply. The methodology is explained by means of a running example.
A flexible exoskeleton for hip assistance
(2017)

This paper proposes a new concept called “a flexible exoskeleton” and presents the design of a wearable walking assistance device to provide physical gait assistance for the elderly. To overcome some limitations of previous wearable walking assistance devices, 3 novel mechanisms are proposed: 1) flexible thigh frames that withstand the designated load direction, 2) an adjustable flexible hip brace surrounding the wearer's body, and 3) slim and backdrivable actuators that minimize the maximum height and resistance. The proposed walking assistance device has reduced metabolic energy consumption by 13.2±4% compared with a free condition.
Using Visual Speech Information in Masking Methods for Audio Speaker Separation
(2018)

This paper examines whether visual speech information can be effective within audio-masking-based speaker separation to improve the quality and intelligibility of the target speech. Two visual-only methods of generating an audio mask for speaker separation are first developed. These use a deep neural network to map the visual speech features to an audio feature space from which both visually derived binary masks and visually derived ratio masks are estimated, before application to the speech mixture. Second, an audio ratio masking method forms a baseline approach for speaker separation which is extended to exploit visual speech information to form audio-visual ratio masks. Speech quality and intelligibility tests are carried out on the visual-only, audio-only, and audio-visual masking methods of speaker separation at mixing levels from $-$ 10 to +10 dB. These reveal substantial improvements in the target speech when applying the visual-only and audio-only masks, but with highest performance occurring when combining audio and visual information to create the audio-visual masks.
Maintaining excellence: deliberate practice and elite performance in young and older pianists.
(1996)

Two studies investigated the role of deliberate practice in the maintenance of cognitive-motor skills in expert and accomplished amateur pianists. Older expert and amateur pianists showed the normal pattern of large age-related reductions in standard measures of general processing speed. Performance on music-related tasks showed similar age-graded decline for amateur pianists but not for expert pianists, whose average performance level was only slightly below that of young expert pianists. The degree of maintenance of relevant pianistic skills for older expert pianists was predicted by the amount of deliberate practice during later adulthood. The role of deliberate practice in the active maintenance of superior domain-specific performance in spite of general age-related decline is discussed.
Learning Multi-level Features For Sensor-based Human Action Recognition
(2017)

This paper proposes amulti-level feature learning framework for human action recognition using a single body-worn inertial sensor. The framework consists of three phases, respectively designed to analyze signal-based (low-level), components (mid-level) and semantic (high-level) information. Low-level features capture the time and frequency domain property while mid-level representations learn the composition of the action. The Maxmargin Latent Pattern Learning (MLPL) method is proposed to learn high-level semantic descriptions of latent action patterns as the output of our framework. The proposedmethod achieves the state-of-the-art performances, 88.7%, 98.8% and 72.6% (weighted F1 score) respectively, on Skoda, WISDM and OPP datasets. © 2017 Elsevier B.V. All rights reserved.
Computer-Aided Cobb Measurement Based on Automatic Detection of Vertebral Slopes Using Deep Neural Network
(2017)

Objective
To develop a computer-aided method that reduces the variability of Cobb angle measurement for scoliosis assessment.


Methods
A deep neural network (DNN) was trained with vertebral patches extracted from spinal model radiographs. The Cobb angle of the spinal curve was calculated automatically from the vertebral slopes predicted by the DNN. Sixty-five in vivo radiographs and 40 model radiographs were analyzed. An experienced surgeon performed manual measurements on the aforementioned radiographs. Two examiners used both the proposed and the manual measurement methods to analyze the aforementioned radiographs.


Results
For model radiographs, the intraclass correlation coefficients were greater than 0.98, and the mean absolute differences were less than 3°. This indicates that the proposed system showed high repeatability for measurements of model radiographs. For the in vivo radiographs, the reliabilities were lower than those from the model radiographs, and the differences between the computer-aided measurement and the manual measurement by the surgeon were higher than 5°.


Conclusion
The variability of Cobb angle measurements can be reduced if the DNN system is trained with enough vertebral patches. Training data of in vivo radiographs must be included to improve the performance of DNN.


Significance
Vertebral slopes can be predicted by DNN. The computer-aided system can be used to perform automatic measurements of Cobb angle, which is used to make reliable and objective assessments of scoliosis.
Do You Feel What I Feel? Social Aspects of Emotions in Twitter Conversations
(2012)

We present a computational framework for understanding the social aspects of emotions in Twitter conversations. Using unannotated data and semisupervised machine learning, we look at emotional transitions, emotional influences among the conversation partners, and patterns in the overall emotional exchanges. We find that conversational partners usually express the same emotion, which we name Emotion accommodation, but when they do not, one of the conversational partners tends to respond with a positive emotion. We also show that tweets containing sympathy, apology, and complaint are significant emotion influencers. We verify the emotion classification part of our framework by a human-annotated corpus.
Concreteness ratings for 40 thousand generally known English word lemmas.
(2014)

Concreteness ratings are presented for 37,058 English words and 2,896 two-word expressions (such as zebra crossing and zoom in), obtained from over 4,000 participants by means of a norming study using Internet crowdsourcing for data collection. Although the instructions stressed that the assessment of word concreteness would be based on experiences involving all senses and motor responses, a comparison with the existing concreteness norms indicates that participants, as before, largely focused on visual and haptic experiences. The reported data set is a subset of a comprehensive list of English lemmas and contains all lemmas known by at least 85 % of the raters. It can be used in future research as a reference list of generally known English lemmas.
On IC traceability via blockchain
(2018)

Traceability of ICs is important for verifying provenance. We present a novel IC traceability scheme based on blockchain. A blockchain is an immutable public record that maintains a continuously-growing list of data records secured from tampering and revision. In the proposed scheme, IC ownership transfer information is recorded and archived in a blockchain. This safe, verifiable method prevents any party from altering or challenging the legitimacy of the information being exchanged. However, we also need to establish correspondence between a record in a public database and the physical device, in an unclonable way. We propose an embedded physically unclonable function (PUF) to establish this correspondence The blockchain ensures the legitimacy of an IC's current owner, while the PUF safeguards against IC counterfeiting and tampering. Our proposed solution combines hardware and software protocols to let supply chain participants authenticate, track, trace, analyze, and provision chips during their entire life cycle.
Load balancing and OpenMP implementation of nested parallelism
(2005)

Many problems have multiple layers of parallelism. The outer-level may consist of few and coarse-grained tasks. Next, each of these tasks may also be rich in parallelism, and be split into a number of fine-grained tasks, which again may consist of even finer subtasks, and so on. Here we argue and demonstrate by examples that utilizing multiple layers of parallelism may give much better scaling than if one restricts oneself to only one level of parallelism. Two non-trivial issues for multi-level parallelism are load balancing and implementation. In this paper we provide an algorithm for finding good distributions of threads to tasks and discuss how to implement nested parallelism in OpenMP. 2005 Elsevier B.V. All rights reserved.
Design of a transmit-receive (T/R) switch in TSMC 180nm RF CMOS process for 2.4GHz transceiver
(2015)

Design and analysis of a RF transmit/receive switch in 180nm CMOS RF process for 2.4GHz transceiver is presented. LC resonance along with stacked gate architecture is presented for designing the T/R switch. The switch exhibited excellent performance in terms of insertion loss, isolation linearity and gain. The switch added minimum noise by itself during the input and output switching and achieved stability throughout the operating rang at 2.4GHz. The designed switch exhibits -48.73dB and -79.04dB insertion loss during receiver and transmitter mode respectively. The isolation between non-used ports is -96.27 in both mode of operation. The designed switch handles more than 20 dBm power at 2.4 GHz frequency.
Situation and Perspective of Knowledge Engineering
(2000)

Knowledge Engineering was in the past primary concerned with building and developing knowledge-based systems, an objective which puts Knowledge Engineering in a niche of the world-wide research efforts at best. This has changed dramatically: Knowledge Engineering is now a key technology in the upcoming knowledge society. Companies are recognizing knowledge as their key assets, which have to be exploited and protected in a fast changing, global and competitive economy. This situation has led to the application of Knowledge Engineering techniques in Knowledge Management. The demand for more efficient (business to) business processes requires the interconnection and interoperation of different information systems. But information integration is not an algorithmic task that is easy to solve: much knowledge is required to resolve the semantic differences of data residing in two information systems. Thus Knowledge Engineering has become a major technqiue for information integration. And, last but not least the fast growing World Wide Web generates an ever increasing demand for more efficient knowledge exploitation and creation techniques. Here again Knowledge Engineering technologies may become the key technology for solving the problem. In this paper we discuss these recent developments and describe our view of the future.
How Taxing is Corruption on International Investors?
(2000)

This paper studies the effect of corruption on foreign direct investment. The sample covers bilateral investment from twelve source countries to 45 host countries. There are two central findings. First, a rise in either the tax rate on multinational firms or the corruption level in a host country reduces inward foreign direct investment (FDI). In a benchmark estimation, an increase in the corruption level from that of Singapore to that of Mexico would have the same negative effect on inward FDI as raising the tax rate by fifty percentage points. Second, American investors are averse to corruption in host countries, but not necessarily more so than average OECD investors, in spite of the U.S. Foreign Corrupt Practices Act of 1977.
On the modelling of publish/subscribe communication systems
(2005)

This paper presents a formal framework of a distributed computation based on a publish/subscribe system. The framework abstracts the system through two delays, namely the subscription/unsubscription delay and the diffusion delay. This abstraction allows one to model concurrent execution of publication and subscription operations without waiting for the stability of the system state and to define a Liveness property which gives the conditions for the presence of a notification event in the global history of the system. This formal framework allows us to analytically define a measure of the effectiveness of a publish/subscribe system, which reflects the percentage of notifications guaranteed by the system to subscribers. A simulation study confirms the validity of the analytical measurements. Copyright c © 2005 John Wiley & Sons, Ltd.
Research on Credit Card Fraud Detection Model Based on Class Weighted Support Vector Machine
(2011)

To deal with credit card fraud, a detection model based on Class Weighted Support Vector Machine was established. Due to large-scale and high dimensions of data, Principal Component Analysis (PCA) was adopted firstly to screen out the main factors from a great deal of indicative attributes in order to reduce the training dimension of SVM effectively. Then according to the characteristics of credit card transactions data which are imbalance, an improved SVM--Imbalance Class Weighted SVM (ICW-SVM) was adopted. With the application and verification in real dataset from bank, it is demonstrated that this model is more suitable for solving credit card fraud detection problem with higher precision and effective than others.
SURVEY ON REVIEW SPAM DETECTION
(2013)

The proliferation of E-commerce sites has made web an excellent source of gathering customer reviews about products; as there is no quality control anyone one can write anything which leads to review spam. This paper previews and reviews the substantial research on Review Spam detection technique. Further it provides state of art depicting some previous attempt to study review spam detection. KeywordsNatural language processing, reviews centric spam detection, reviewer centric spam detection
The CMU Pose, Illumination, and Expression (PIE) Database
(2002)

Between October 2000 and December 2000 we collected a database of over 40,000 facial images of 68 people. Using the CMU 3D Room we imaged each person across 13 different poses, under 43 different illumination conditions, and with 4 different expressions. We call this database the CMU Pose, Illumination, and Expression (PIE) database. In this paper we describe the imaging hardware, the collection procedure, the organization of the database, several potential uses of the database, and how to obtain the database.